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Unsupervised learning for general and multimodal multimedia retrieval

Grant number: 20/03311-0
Support type:Scholarships in Brazil - Master
Effective date (Start): April 01, 2020
Effective date (End): March 31, 2022
Field of knowledge:Physical Sciences and Mathematics - Computer Science
Principal Investigator:Daniel Carlos Guimarães Pedronette
Grantee:Lucas Barbosa de Almeida
Home Institution: Instituto de Geociências e Ciências Exatas (IGCE). Universidade Estadual Paulista (UNESP). Campus de Rio Claro. Rio Claro , SP, Brazil
Associated research grant:18/15597-6 - Aplication and investigation of unsupervised learning methods in retrieval and classification tasks, AP.JP2


Rank-based Unsupervised Learning Methods have been established as a solution to increase the effectiveness of content-based searches without requiring user intervention. These methods exploit contextual relationships among images, usually encoded in the distance/similarity information of the collections. Recent related work has shown that such methods can also be applied in other retrieval scenarios, involving multimedia data, such as audio and video. The objective of this research project is to investigate the use of unsupervised learning methods for multimodal retrieval, combining several types of data, such as: audio, visual and movement. (AU)